Genotype–Phenotype Correlations in PRPH2 Retinopathies: A Comprehensive Analysis of 36 Patients from the Oxford Eye Hospital, UK
Bibliographic record
Abstract
Purpose: To investigate genotype–phenotype correlations in PRPH2-retinopathies in a cohort of 36 patients from the Oxford Eye Hospital and report on novel pathogenic variants. Methods: Clinical data, including best corrected visual acuities (BCVA), fundus autofluorescence (FAF), and optical coherence tomography (OCT) imaging, were analysed. Genetic testing was performed using next-generation sequencing (NGS). Results: In this cohort, 26 different PRPH2 variants, including 8 novel variants, were identified. Variants were clustered in the D2 loop of the protein. A diverse range of phenotypes were observed: pseudo-Stargardt pattern dystrophy (PSPD) (47.2%), adult-onset vitelliform macular dystrophy (AVMD) (22.2%), pattern dystrophy (PD) (25.0%), atypical macular dystrophy (2.8%), and retinitis pigmentosa (RP) (2.8%). The mean age of symptom onset was 44.0 ± 14.4 years. Mean BCVA was 0.20 ± 0.54 logMAR OD and 0.14 ± 0.29 logMAR OS at baseline and 0.33 ± 0.40 logMAR OD and 0.32 ± 0.40 logMAR OS after a mean follow up duration of 6.0 ± 3.2 years (range 1–11 years). A thickened ellipsoid zone (EZ) was noted in 34/36 patients with a mean EZ thickness of 44.3 ± 11.3 µm OD and 42.7 ± 11.6 µm OS. No clear genotype–phenotype correlations were observed. Conclusions: The significant phenotypic range described in this study is consistent with the previously reported phenotypic variability in PRPH2 retinopathy and emphasises the complexity of establishing genotype–phenotype correlations in this disease. The thickness of the EZ on OCT may serve as a useful biomarker in distinguishing PRPH2 retinopathy from other phenocopies. These findings contribute to improved understanding of PRPH2 retinopathy and help inform diagnosis and genetic counselling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".